A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 10, 10:15 UTC
[Model] Remove redundant None check in DeepSeekOCR image input processing (#32016)
Signed-off-by: maang <maang_h@163.com>
maang committed
Jan 9, 2026 at 22:12 UTC
7cdf7e2fe0d406724659d84e0a17fde97f855a89
1 file changed
+10
-13
vllm/model_executor/models/deepseek_ocr.py
+10
-13
@@ -438,19 +438,16 @@ class DeepseekOCRForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, Supports
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if pixel_values is None or torch.sum(pixel_values).item() == 0:
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return None
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- if pixel_values is not None:
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- base_size = self.vision_config.image_size
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- return DeepseekOCRImagePixelInputs(
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- type="pixel_values",
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- data=pixel_values,
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- images_crop=images_crop,
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- images_spatial_crop=images_spatial_crop,
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- resolve_bindings={
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- "base_size": base_size,
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- },
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- )
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-
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- raise AssertionError("This line should be unreachable.")
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+ base_size = self.vision_config.image_size
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+ return DeepseekOCRImagePixelInputs(
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+ type="pixel_values",
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+ data=pixel_values,
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+ images_crop=images_crop,
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+ images_spatial_crop=images_spatial_crop,
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+ resolve_bindings={
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+ "base_size": base_size,
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+ },
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+ )
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def _encode_global_features(self, image_tensor: torch.Tensor) -> torch.Tensor:
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global_features_1 = self.sam_model(image_tensor)